Real‐time biofeedback integrated into neuromuscular training reduces high‐risk knee biomechanics and increases functional brain connectivity: A preliminary longitudinal investigation

Prospective evidence indicates that functional biomechanics and brain connectivity may predispose an athlete to an anterior cruciate ligament injury, revealing novel neural linkages for targeted neuromuscular training interventions. The purpose of this study was to determine the efficacy of a real‐time biofeedback system for altering knee biomechanics and brain functional connectivity. Seventeen healthy, young, physically active female athletes completed 6 weeks of augmented neuromuscular training (aNMT) utilizing real‐time, interactive visual biofeedback and 13 served as untrained controls. A drop vertical jump and resting state functional magnetic resonance imaging were separately completed at pre‐ and posttest time points to assess sensorimotor adaptation. The aNMT group had a significant reduction in peak knee abduction moment (pKAM) compared to controls (p = .03, d = 0.71). The aNMT group also exhibited a significant increase in functional connectivity between the right supplementary motor area and the left thalamus (p = .0473 after false discovery rate correction). Greater percent change in pKAM was also related to increased connectivity between the right cerebellum and right thalamus for the aNMT group (p = .0292 after false discovery rate correction, r2 = .62). No significant changes were observed for the controls (ps > .05). Our data provide preliminary evidence of potential neural mechanisms for aNMT‐induced motor adaptations that reduce injury risk. Future research is warranted to understand the role of neuromuscular training alone and how each component of aNMT influences biomechanics and functional connectivity.Emergent evidence indicates that the risk of anterior cruciate ligament (ACL) injury is, in part, due to central nervous system alterations that could be targeted using neural mechanistic sensorimotor‐based treatments. Young female athletes completed 6 weeks of neuromuscular training while interacting with a real‐time, visual biofeedback stimulus. Our training was designed to reduce the risk of by (a) promoting injury‐resistant movement and (b) strengthening brain functional connectivity. Our data not only indicated that athletes’ biomechanics and brain connectivity were improved following training, but the observed biomechanical improvements were related to distinct, strengthened connectivity within regions important for sensorimotor control. This study supports the use of real‐time biofeedback systems to reduce the risk of ACL injury by leveraging neuroplasticity.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154933/1/psyp13545_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154933/2/psyp13545.pd

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

The Effects of External Jugular Compression Applied during Head Impact Exposure on Longitudinal Changes in Brain Neuroanatomical and Neurophysiological Biomarkers: A Preliminary Investigation

Objectives: Utilize a prospective in vivo clinical trial to evaluate the potential for mild neck compression applied during head impact exposure to reduce anatomical and physiological biomarkers of brain injury. Methods: This project utilized a prospective randomized controlled trial to evaluate effects of mild jugular vein (neck) compression (collar) relative to controls (no collar) during a competitive hockey season (males; 16.3 ± 1.2 years). The collar was designed to mildly compress the jugular vein bilaterally with the goal to increase intracranial blood volume to reduce risk of brain slosh injury during head impact exposure. Helmet sensors were used to collect daily impact data in excess of 20 g (games and practices) and the primary outcome measures, which included changes in white matter (WM) microstructure, were assessed by diffusion tensor imaging (DTI). Specifically, four DTI measures: fractional anisotropy, mean diffusivity (MD), axial diffusivity, and radial diffusivity (RD) were used in the study. These metrics were analyzed using the tract-based Spatial Statistics (TBSS) approach – a voxel-based analysis. In addition, electroencephalography-derived event-related potentials were used to assess changes in brain network activation (BNA) between study groups. Results: For athletes not wearing the collar, DTI measures corresponding to a disruption of WM microstructure, including MD and RD, increased significantly from pre-season to mid-season (p 0.05). In addition to these anatomical findings, electrophysiological network analysis of the degree of congruence in the network electrophysiological activation pattern demonstrated concomitant changes in brain network dynamics in the non-collar group only (p < 0.05). Similar to the DTI findings, the increased change in BNA score in the non-collar relative to the collar group was statistically significant (p < 0.01). Changes in DTI outcomes were also directly correlated with altered brain network dynamics (r = 0.76; p < 0.05) as measured by BNA. Conclusion: Group differences in the longitudinal changes in both neuroanatomical and electrophysiological measures, as well as the correlation between the measures, provide initial evidence indicating that mild jugular vein compression may have reduced alterations in the WM response to head impacts during a competitive hockey season. The data indicate sport-related alterations in WM microstructure were ameliorated by application of jugular compression during head impact exposure. These results may lead to a novel line of research inquiry to evaluate the effects of protecting the brain from sports-related head impacts via optimized intracranial fluid dynamics

Business model innovation for eco-efficiency: an empirical study

Business model has the potential to create value and capture value for companies, which is critical for their sustainable development [1]. The concept of eco-efficiency can be a useful concept to link an enterprise’s business with sustainable development as well as achieving long-term profits [2,3]. Extant lit- erature reveals that there is a need to study business model innovation and eco- efficiency under one text to achieve a win-win rationale to increase profits while reducing environmental impact [4,5]. This empirical study conducted 8-in-depth case studies with manufacturing companies across UK and China. The author synthesized the cases and concluded the measures of business model innovation for eco-efficiency in five categories, namely (1) Selling of service model, (2) Direct selling model, (3) Collaboration strategy, (4) Whole system design strat- egy, and (5) Technology renovation strategy. The empirical finding suggests the adaptation of strategy and exploitation of the technologies are essential to busi- ness model innovation when manufacturing companies seeking to implement eco-efficiency

Economic Analysis of Knowledge: The History of Thought and the Central Themes

Following the development of knowledge economies, there has been a rapid expansion of economic analysis of knowledge, both in the context of technological knowledge in particular and the decision theory in general. This paper surveys this literature by identifying the main themes and contributions and outlines the future prospects of the discipline. The wide scope of knowledge related questions in terms of applicability and alternative approaches has led to the fragmentation of research. Nevertheless, one can identify a continuing tradition which analyses various aspects of the generation, dissemination and use of knowledge in the economy

Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society\u27s responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak

Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

Background: Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods: We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results: Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion: Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening

The genomic basis of parasitism in the Strongyloides clade of nematodes.

Soil-transmitted nematodes, including the Strongyloides genus, cause one of the most prevalent neglected tropical diseases. Here we compare the genomes of four Strongyloides species, including the human pathogen Strongyloides stercoralis, and their close relatives that are facultatively parasitic (Parastrongyloides trichosuri) and free-living (Rhabditophanes sp. KR3021). A significant paralogous expansion of key gene families--families encoding astacin-like and SCP/TAPS proteins--is associated with the evolution of parasitism in this clade. Exploiting the unique Strongyloides life cycle, we compare the transcriptomes of the parasitic and free-living stages and find that these same gene families are upregulated in the parasitic stages, underscoring their role in nematode parasitism